Equivalence of the $Q(s,a)$ and $V(s)$ under optimality conditions?
In general they are not the same and that should be clear as to why -- mathematically you are conditioning on an extra random variable being known in the state-action value function. You have the correct relationship between them, but I think your understanding of the two may be slightly off. The state-action value function is a function of both $s$ and $a$ whereas the value function is a function of just $s$. As you have noted, the value function is equal to the expected value of the state-action value function, with the expectation taken over the action distribution induced by the policy.
However, if you have a deterministic policy, then two are equivalent only if you evaluate the state-action value function at the action that the deterministic policy gives. That is, $v_\pi(s) = Q(s, \pi(s))$. This is because, as you say, for a given state the policy will assign probability one to a certain action and 0 to all other actions in the action space and so the equation I just wrote is what the expectation in your question reduces to.
Now, you might think 'well the policy is deterministic so we are always going to choose this action, so my theory was correct'. This is not true. The definition of the state-action value function is the value of the expected future (possibly discounted) returns given that we are in state $s$ and given that we have taken action $a$. This means that we have already chosen our action and we are not choosing it according to the policy -- the policy will only choose all future actions.
You also say that &quot;If we are operating a greedy policy and hence acting optimally&quot; which is not true. Just because we act greedily it does not imply we are acting optimally. Value functions are functions of a policy. If the policy is completely random then you would get certain value and state-action value functions which you could act greedily to but this would not be optimal.